CGP

Composite Gaussian Process Models

Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.

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Package

CGP

Type

Package

Title

Composite Gaussian Process Models

Version

2.1-1

Date

2018-06-11

Author

Shan Ba and V. Roshan Joseph

Maintainer

Shan Ba

Description

Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) "Composite Gaussian Process Models for Emulating Expensive Functions", Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.

License

LGPL-2.1

NeedsCompilation

no

Packaged

2018-06-12 14:20:18 UTC; ba.s

Repository

CRAN

Date/Publication

2018-06-12 15:08:19 UTC

install.packages('CGP')

2.1-1

7 months ago

Shan Ba

LGPL-2.1

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